Incremental Nonlinear Dynamic Inversion based Optical Flow Control for Flying Robots: An Efficient Data-driven Approach

TL;DR

This paper introduces an efficient data-driven incremental nonlinear dynamic inversion control method for optical flow-based flight control of MAVs, improving robustness and real-time performance in dynamic environments.

Contribution

It proposes a novel INDI control scheme that estimates control effectiveness inverses in real-time, handling nonlinear optical flow observables without high computational costs.

Findings

Successfully demonstrated in simulations and real-world tests

Achieved precise landings on static and moving surfaces

Robust to noisy optical flow estimates and surface movements

Abstract

This paper presents a novel approach for optical flow control of Micro Air Vehicles (MAVs). The task is challenging due to the nonlinearity of optical flow observables. Our proposed Incremental Nonlinear Dynamic Inversion (INDI) control scheme incorporates an efficient data-driven method to address the nonlinearity. It directly estimates the inverse of the time-varying control effectiveness in real-time, eliminating the need for the constant assumption and avoiding high computation in traditional INDI. This approach effectively handles fast-changing system dynamics commonly encountered in optical flow control, particularly height-dependent changes. We demonstrate the robustness and efficiency of the proposed control scheme in numerical simulations and also real-world flight tests: multiple landings of an MAV on a static and flat surface with various tracking setpoints, hovering and landings on moving and undulating surfaces. Despite being challenged with the presence of noisy optical flow estimates and the lateral and vertical movement of the landing surfaces, the MAV is able to successfully track or land on the surface with an exponential decay of both height and vertical velocity at almost the same time, as desired.